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Register a new userCalorimetry for low-energy electrons using charge and light in liquid argon
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Precise calorimetric reconstruction of 5-50 MeV electrons in liquid argon time projection chambers (LArTPCs) will enable the study of astrophysical neutrinos in DUNE and could enhance the physics reach of oscillation analyses. Liquid argon scintillation light has the potential to improve energy reconstruction for low-energy electrons over charge-based measurements alone. Here we demonstrate light-augmented calorimetry for low-energy electrons in a single-phase LArTPC using a sample of Michel electrons from decays of stopping cosmic muons in the LArIAT experiment at Fermilab. Michel electron energy spectra are reconstructed using both a traditional charge-based approach as well as a more holistic approach that incorporates both charge and light. A maximum-likelihood fitter, using LArIATs well-tuned simulation, is developed for combining these quantities to achieve optimal energy resolution. A sample of isolated electrons is simulated to better determine the energy resolution expected for astrophysical electron-neutrino charged-current interaction final states. In LArIAT, which has very low wire noise and an average light yield of 18 pe/MeV, an energy resolution of $sigma/E simeq 9.3%/sqrt{E} oplus 1.3%$ is achieved. Samples are then generated with varying wire noise levels and light yields to gauge the impact of light-augmented calorimetry in larger LArTPCs. At a charge-readout signal-to-noise of S/N $simeq$ 30, for example, the energy resolution for electrons below 40 MeV is improved by $approx$ 10%, $approx$ 20%, and $approx$ 40% over charge-only calorimetry for average light yields of 10 pe/MeV, 20 pe/MeV, and 100 pe/MeV, respectively.
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We report the demonstration of a low-power pixelated readout system designed for three-dimensional ionization charge detection and digital readout of liquid argon time projection chambers (LArTPCs). Unambiguous 3D charge readout was achieved using a custom-designed system-on-a-chip ASIC (LArPix) to uniquely instrument each pad in a pixelated array of charge-collection pads. The LArPix ASIC, manufactured in 180 nm bulk CMOS, provides 32 channels of charge-sensitive amplification with self-triggered digitization and multiplexed readout at temperatures from 80 K to 300 K. Using an 832-channel LArPix-based readout system with 3 mm spacing between pads, we demonstrated low-noise ($<$500 e$^-$ RMS equivalent noise charge) and very low-power ($<$100 $mu$W/channel) ionization signal detection and readout. The readout was used to successfully measure the three-dimensional ionization distributions of cosmic rays passing through a LArTPC, free from the ambiguities of existing projective techniques. The system design relies on standard printed circuit board manufacturing techniques, enabling scalable and low-cost production of large-area readout systems using common commercial facilities. This demonstration overcomes a critical technical obstacle for operation of LArTPCs in high-occupancy environments, such as the near detector site of the Deep Underground Neutrino Experiment (DUNE).
The liquid argon ionization current in a sampling calorimeter cell can be analyzed to determine the energy of detected particles. In practice, experimental artifacts such as pileup and electronic noise make the inference of energy from current a difficult process. The beam intensity of the Large Hadron Collider will be significantly increased during the Phase-II long shut down of 2024-2026. Signal processing techniques that are used to extract the energy of detected particles in the ATLAS detector will suffer a significant loss in performance under these conditions. This paper compares the presently used optimal filter technique to convolutional neural networks for energy reconstruction in the ATLAS liquid argon hadronic end cap calorimeter. In particular, it is shown that convolutional neural networks trained with an appropriately tuned and novel loss function are able to outperform the optimal filter technique.
Liquid argon is used as active medium in a variety of neutrino and Dark Matter experiments thanks to its excellent properties of charge yield and transport and as a scintillator. Liquid argon scintillation photons are emitted in a narrow band of 10~nm centered around 127 nm and with a characteristic time profile made by two components originated by the decay of the lowest lying singlet and triplet state of the excimer Ar$_2^*$ to the dissociative ground state. A model is proposed which takes into account the quenching of the long lived triplet states through the self-interaction with other triplet states or through the interaction with molecular Ar$_2^+$ ions. The model predicts the time profile of the scintillation signals and its dependence on the intensity of an external electric field and on the density of deposited energy, if the relative abundance of the unquenched fast and slow components is know. The model successfully explains the experimentally observed dependence of the characteristic time of the slow component on the intensity of the applied electric field and the increase of photon yield of liquid argon when doped with small quantities of xenon (at the ppm level). The model also predicts the dependence of the pulse shape parameter, F$_{prompt}$, for electron and nuclear recoils on the recoil energy and the behavior of the relative light yield of nuclear recoils in liquid argon, $mathcal{L}_{eff}$
An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.
Scintillation light produced in liquid argon (LAr) must be shifted from 128 nm to visible wavelengths in light detection systems used for liquid argon time-projection chambers (LArTPCs). To date, LArTPC light collection systems have employed tetraphenyl butadiene (TPB) coatings on photomultiplier tubes (PMTs) or plates placed in front of the PMTs. Recently, a new approach using TPB-coated light guides was proposed. In this paper, we report on light guides with improved attenuation lengths above 100 cm when measured in air. This is an important step in the development of meter-scale light guides for future LArTPCs. Improvements come from using a new acrylic-based coating, diamond-polished cast UV transmitting acrylic bars, and a hand-dipping technique to coat the bars. We discuss a model for connecting bar response in air to response in liquid argon and compare this to data taken in liquid argon. The good agreement between the prediction of the model and the measured response in liquid argon demonstrates that characterization in air is sufficient for quality control of bar production. This model can be used in simulations of light guides for future experiments.
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